A K-Means Clustering Algorithm to Determine Representative Operational Profiles of a Ship Using AIS Data

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Abstract

Defining the appropriate functional requirements in the early ship design stage is important in order that costs that are caused by the over- or under-specified functional capabilities do not increase. This paper presents a K-means clustering algorithm for the determination of functional requirements. It uses automatic identification system (AIS) data from a reference ship to determine the representative operational profiles, which can support decision-makers in defining the functional requirements of ships that will be performing similar missions as those of the reference ship. In a case study, we used this method as part of a ship design project, in which the functional requirements of a battery-only electric ship are defined using AIS data from a reference ship. Results indicate that the cost can be reduced by determining the functional requirements using the proposed method.

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Park, J., & Choi, M. (2022). A K-Means Clustering Algorithm to Determine Representative Operational Profiles of a Ship Using AIS Data. Journal of Marine Science and Engineering, 10(9). https://doi.org/10.3390/jmse10091245

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